To reproduce this run, first install NVIDIA NeMo according to the official instructions, then execute:

#!/usr/bin/env bash
CUDA_VISIBLE_DEVICES=0 python run_speech_recognition_rnnt.py \
 --config_path="conf/conformer_transducer_bpe_xlarge.yaml" \
 --model_name_or_path="stt_en_conformer_transducer_xlarge" \
 --dataset_name="esb/datasets" \
 --tokenizer_path="tokenizer" \
 --vocab_size="1024" \
 --max_steps="100000" \
 --dataset_config_name="voxpopuli" \
 --output_dir="./" \
 --run_name="conformer-rnnt-voxpopuli" \
 --wandb_project="rnnt" \
 --per_device_train_batch_size="8" \
 --per_device_eval_batch_size="4" \
 --logging_steps="50" \
 --learning_rate="1e-4" \
 --warmup_steps="500" \
 --save_strategy="steps" \
 --save_steps="20000" \
 --evaluation_strategy="steps" \
 --eval_steps="20000" \
 --report_to="wandb" \
 --preprocessing_num_workers="4" \
 --fused_batch_size="4" \
 --length_column_name="input_lengths" \
 --fuse_loss_wer \
 --group_by_length \
 --overwrite_output_dir \
 --do_train \
 --do_eval \
 --do_predict \
 --use_auth_token